Here are preliminary results of the bibliometric mapping of the 2022 Luxembourg research evaluation. Its purpose is:
The method for the research-field-mapping can be reviewed here:
The seed articles deemed representative for the active areas of research in the institution, and include authors affiliated with the institution. They can be selected in three ways:
The present analysis is based on the following seed articles:
| AU | PY | TI | JI |
|---|---|---|---|
| WÓJCIK D;URBAN M;DÖRRY S | 2022 | LUXEMBOURG AND IRELAND IN GLOBAL FINANCIAL NETWORKS: ANALYSING THE CHANGING STRUCTURE OF EUROPEAN… | TRANS. INST. BR. GEOGR. |
| GLUMAC B;DES ROSIERS F | 2020 | PRACTICE BRIEFING – AUTOMATED VALUATION MODELS (AVMS): THEIR ROLE, THEIR ADVANTAGES AND THEIR LIM… | J. PROP. INVEST. FINAN. |
| BURZYNSKI M;DEUSTER C;DOCQU… | 2020 | GEOGRAPHY OF SKILLS AND GLOBAL INEQUALITY | J. DEV. ECON. |
| DECOVILLE A;DURAND F | 2019 | EXPLORING CROSS-BORDER INTEGRATION IN EUROPE: HOW DO POPULATIONS CROSS BORDERS AND PERCEIVE THEIR… | EUR. URBAN REG. STUD. |
| DE VOS J;SCHWANEN T;VAN ACK… | 2019 | DO SATISFYING WALKING AND CYCLING TRIPS RESULT IN MORE FUTURE TRIPS WITH ACTIVE TRAVEL MODES? AN … | INTL. J. SUSTAINABLE TRANSP. |
| TAYYEBI A;TAYYEBI AH;PEKIN … | 2018 | MODELING HISTORICAL LAND USE CHANGES AT A REGIONAL SCALE: APPLYING QUANTITY AND LOCATIONAL ERROR … | J. ENVIRON. INF. |
| LAMOUR C | 2017 | THE NEO-WESTPHALIAN PUBLIC SPHERE OF LUXEMBOURG: THE REBORDERING OF A MEDIATED STATE DEMOCRACY IN… | TIJDSCHR. ECON. SOC. GEOGR. |
| CARLIN A;PERCHOUX C;PUGGINA… | 2017 | A LIFE COURSE EXAMINATION OF THE PHYSICAL ENVIRONMENTAL DETERMINANTS OF PHYSICAL ACTIVITY BEHAVIO… | PLOS ONE |
Here, we report the results of a LDA topic-modelling (basically, clustering on words) on all title+abstract texts.
Note: While this static vies is helpful, I recommend using the interactive LDAVis version to be found under https://daniel-hain.github.io/biblio_lux_2022/output/topic_modelling/LDAviz_liser_ud.rds/index.html#topic=1&lambda=0.60&term=. For functionality and usage, see technical description in the next tab.
Topic modeling is a type of statistical modeling for discovering the abstract “topics” that occur in a collection of documents. Latent Dirichlet Allocation (LDA, Blei et al., 2003) is an example of topic model and is used to classify text in a document to a particular topic.
LDA is a generative probabilistic model that assumes each topic is a mixture over an underlying set of words, and each document is a mixture of over a set of topic probabilities. It builds a topic per document model and words per topic model, modeled as Dirichlet distributions.
LDAvis is a web-based interactive visualisation of topics estimated using LDA (Sievert & Shirley, 2014). It provides a global view of the topics (and how they differ from each other), while at the same time allowing for a deep inspection of the terms most highly associated with each individual topic. The package extracts information from a fitted LDA topic model to inform an interactive web-based visualization. The visualisation has two basic pieces.
The left panel visualise the topics as circles in the two-dimensional plane whose centres are determined by computing the Jensen–Shannon divergence between topics, and then by using multidimensional scaling to project the inter-topic distances onto two dimensions. Each topic’s overall prevalence is encoded using the areas of the circles.
The right panel depicts a horizontal bar chart whose bars represent the individual terms that are the most useful for interpreting the currently selected topic on the left. A pair of overlaid bars represent both the corpus-wide frequency of a given term as well as the topic-specific frequency of the term.
The \(\lambda\) slider allows to rank the terms according to term relevance. By default, the terms of a topic are ranked in decreasing order according their topic-specific probability ( \(\lambda\) = 1 ). Moving the slider allows to adjust the rank of terms based on much discriminatory (or “relevant”) are for the specific topic. The suggested optimal value of \(\lambda\) is 0.6.
Note: This analysis refers the co-citation analysis,
where the cited references and not the original publications are the
unit of analysis. See tab Technical descriptionfor
additional explanations
In order to partition networks into components or clusters, we deploy a community detection technique based on the Lovain Algorithm (Blondel et al., 2008). The Lovain Algorithm is a heuristic method that attempts to optimize the modularity of communities within a network by maximizing within- and minimizing between-community connectivity. We identify the following communities = knowledge bases.
| name | dgr_int | dgr |
|---|---|---|
| Knowledge Base 1: KB 1: Physical activities, health (n = 1943, density =1.98) | ||
| JANSSEN I. LEBLANC A.G. SYSTEMATIC REVIEW OF THE HEALTH BENEFITS OF PHYSICAL ACTIVITY AND FITNESS IN SCHOOL-AGED CHILDREN AND YOUTH (2010) | 3129 | 3144 |
| SAELENS B.E. HANDY S.L. BUILT ENVIRONMENT CORRELATES OF WALKING: A REVIEW (2008) | 2198 | 2770 |
| HALLAL P.C. ANDERSEN L.B. BULL F.C. GUTHOLD R. HASKELL W. EKELUND U. GLOBAL PHYSICAL ACTIVITY LEVELS: SURVEILLANCE PROGRESS PITFALLS AND PROSPECTS … | 2074 | 2097 |
| SALLIS J.F. CERVERO R.B. ASCHER W. HENDERSON K.A. KRAFT M.K. KERR J. AN ECOLOGICAL APPROACH TO CREATING ACTIVE LIVING COMMUNITIES (2006) | 2058 | 2113 |
| SAELENS B.E. SALLIS J.F. FRANK L.D. ENVIRONMENTAL CORRELATES OF WALKING AND CYCLING: FINDINGS FROM THE TRANSPORTATION URBAN DESIGN AND PLANNING LIT… | 1577 | 2124 |
| MCCORMACK G.R. SHIELL A. IN SEARCH OF CAUSALITY: A SYSTEMATIC REVIEW OF THE RELATIONSHIP BETWEEN THE BUILT ENVIRONMENT AND PHYSICAL ACTIVITY AMONG … | 1372 | 1477 |
| SALLIS J.F. PROCHASKA J.J. TAYLOR W.C. A REVIEW OF CORRELATES OF PHYSICAL ACTIVITY OF CHILDREN AND ADOLESCENTS (2000) | 1289 | 1289 |
| SAELENS B.E. SALLIS J.F. BLACK J.B. CHEN D. NEIGHBORHOOD-BASED DIFFERENCES IN PHYSICAL ACTIVITY: AN ENVIRONMENT SCALE EVALUATION (2003) | 907 | 1004 |
| EVENSON K.R. CATELLIER D.J. GILL K. ONDRAK K.S. MCMURRAY R.G. CALIBRATION OF TWO OBJECTIVE MEASURES OF PHYSICAL ACTIVITY FOR CHILDREN (2008) | 838 | 838 |
| DING D. SALLIS J.F. KERR J. LEE S. ROSENBERG D.E. NEIGHBORHOOD ENVIRONMENT AND PHYSICAL ACTIVITY AMONG YOUTH: A REVIEW (2011) | 778 | 781 |
| Knowledge Base 2: KB 2: Travel behaviour, built environment (n = 1173, density =6.15) | ||
| CERVERO R. KOCKELMAN K. TRAVEL DEMAND AND THE 3DS: DENSITY DIVERSITY AND DESIGN (1997) | 3634 | 5330 |
| EWING R. CERVERO R. TRAVEL AND THE BUILT ENVIRONMENT: A META-ANALYSIS (2010) | 2739 | 3756 |
| MOKHTARIAN P.L. CAO X. EXAMINING THE IMPACTS OF RESIDENTIAL SELF-SELECTION ON TRAVEL BEHAVIOR: A FOCUS ON METHODOLOGIES (2008) | 2330 | 2699 |
| HANDY S. CAO X. MOKHTARIAN P. CORRELATION OR CAUSALITY BETWEEN THE BUILT ENVIRONMENT AND TRAVEL BEHAVIOR? EVIDENCE FROM NORTHERN CALIFORNIA (2005) | 1885 | 2188 |
| EWING R. CERVERO R. TRAVEL AND THE BUILT ENVIRONMENT (2010) | 1813 | 2437 |
| EWING R. CERVERO R. TRAVEL AND THE BUILT ENVIRONMENT: A SYNTHESIS (2001) | 1794 | 2268 |
| CAO X. MOKHTARIAN P.L. HANDY S.L. EXAMINING THE IMPACTS OF RESIDENTIAL SELF-SELECTION ON TRAVEL BEHAVIOUR: A FOCUS ON EMPIRICAL FINDINGS (2009) | 1618 | 2149 |
| BHAT C.R. GUO J.Y. A COMPREHENSIVE ANALYSIS OF BUILT ENVIRONMENT CHARACTERISTICS ON HOUSEHOLD RESIDENTIAL CHOICE AND AUTO OWNERSHIP LEVELS (2007) | 1545 | 1590 |
| BAGLEY M.N. MOKHTARIAN P.L. THE IMPACT OF RESIDENTIAL NEIGHBORHOOD TYPE ON TRAVEL BEHAVIOR: A STRUCTURAL EQUATIONS MODELING APPROACH (2002) | 1366 | 1711 |
| VAN ACKER V. WITLOX F. CAR OWNERSHIP AS A MEDIATING VARIABLE IN CAR TRAVEL BEHAVIOUR RESEARCH USING A STRUCTURAL EQUATION MODELLING APPROACH TO IDE… | 1140 | 1182 |
| Knowledge Base 3: KB 3: Economic growth (n = 1059, density =4.45) | ||
| SOLOW R.M. A CONTRIBUTION TO THE THEORY OF ECONOMIC GROWTH (1956) | 1504 | 1509 |
| LUCAS R.E. ON THE MECHANICS OF ECONOMIC DEVELOPMENT (1988) | 1345 | 1361 |
| ROMER P.M. ENDOGENOUS TECHNOLOGICAL CHANGE (1990) | 988 | 991 |
| MANKIW N.G. ROMER D. WEIL D.N. A CONTRIBUTION TO THE EMPIRICS OF ECONOMIC GROWTH (1992) | 896 | 896 |
| HALL R.E. JONES C.I. WHY DO SOME COUNTRIES PRODUCE SO MUCH MORE OUTPUT PER WORKER THAN OTHERS? (1999) | 800 | 800 |
| BARRO R.J. ECONOMIC GROWTH IN A CROSS SECTION OF COUNTRIES (1991) | 765 | 765 |
| ROMER P.M. INCREASING RETURNS AND LONG-RUN GROWTH (1986) | 711 | 714 |
| GALOR O. ZEIRA J. INCOME DISTRIBUTION AND MACROECONOMICS (1993) | 618 | 627 |
| BLUNDELL R. BOND S. INITIAL CONDITIONS AND MOMENT RESTRICTIONS IN DYNAMIC PANEL DATA MODELS (1998) | 578 | 578 |
| GALOR O. (2011) | 570 | 570 |
| Knowledge Base 4: KB 4: Modelling land use changes (n = 937, density =5.06) | ||
| WU F. CALIBRATION OF STOCHASTIC CELLULAR AUTOMATA: THE APPLICATION TO RURAL-URBAN LAND CONVERSIONS (2002) | 1238 | 1238 |
| PIJANOWSKI B.C. BROWN D.G. SHELLITO B.A. MANIK G.A. USING NEURAL NETWORKS AND GIS TO FORECAST LAND USE CHANGES: A LAND TRANSFORMATION MODEL (2002) | 1041 | 1041 |
| CLARKE K.C. HOPPEN S. GAYDOS L. A SELF-MODIFYING CELLULAR AUTOMATON MODEL OF HISTORICAL URBANIZATION IN THE SAN FRANCISCO BAY AREA (1997) | 1035 | 1038 |
| CLARKE K.C. GAYDOS L.J. LOOSE-COUPLING A CELLULAR AUTOMATON MODEL AND GIS: LONG-TERM URBAN GROWTH PREDICTION FOR SAN FRANCISCO AND WASHINGTON/BALTI… | 890 | 890 |
| SILVA E.A. CLARKE K.C. CALIBRATION OF THE SLEUTH URBAN GROWTH MODEL FOR LISBON AND PORTO PORTUGAL (2002) | 744 | 744 |
| WHITE R. ENGELEN G. CELLULAR AUTOMATA AND FRACTAL URBAN FORM: A CELLULAR MODELLING APPROACH TO THE EVOLUTION OF URBAN LAND-USE PATTERNS (1993) | 737 | 737 |
| TAYYEBI A. PIJANOWSKI B.C. MODELING MULTIPLE LAND USE CHANGES USING ANN CART AND MARS: COMPARING TRADEOFFS IN GOODNESS OF FIT AND EXPLANATORY POWER… | 702 | 705 |
| YANG Q. LI X. SHI X. CELLULAR AUTOMATA FOR SIMULATING LAND USE CHANGES BASED ON SUPPORT VECTOR MACHINES (2008) | 688 | 688 |
| WU F. WEBSTER C.J. SIMULATION OF LAND DEVELOPMENT THROUGH THE INTEGRATION OF CELLULAR AUTOMATA AND MULTICRITERIA EVALUATION (1998) | 664 | 664 |
| PONTIUS R.G. MILLONES M. DEATH TO KAPPA: BIRTH OF QUANTITY DISAGREEMENT AND ALLOCATION DISAGREEMENT FOR ACCURACY ASSESSMENT (2011) | 604 | 604 |
| Knowledge Base 5: KB 5: Financial geography (n = 746, density =4.4) | ||
| LANGLEY P. (2008) | 2597 | 2670 |
| MARTIN R. (2002) | 1011 | 1021 |
| FRENCH S. LEYSHON A. WAINWRIGHT T. FINANCIALIZING SPACE SPACING FINANCIALIZATION (2011) | 394 | 401 |
| VAN DER ZWAN N. MAKING SENSE OF FINANCIALIZATION (2014) | 390 | 397 |
| HARVEY D. (2005) | 352 | 373 |
| CHRISTOPHERS B. THE LIMITS TO FINANCIALIZATION (2015) | 325 | 325 |
| AALBERS M.B. THE FINANCIALIZATION OF HOME AND THE MORTGAGE MARKET CRISIS (2008) | 281 | 281 |
| FINLAYSON A. FINANCIALISATION FINANCIAL LITERACY AND ASSET-BASED WELFARE (2009) | 257 | 257 |
| HARVEY D. (1982) | 232 | 241 |
| PIKE A. POLLARD J. ECONOMIC GEOGRAPHIES OF FINANCIALIZATION (2010) | 229 | 244 |
| Knowledge Base 6: KB 6: Satisfaction with travel (n = 679, density =15.77) | ||
| OLSSON L.E. GÄRLING T. ETTEMA D. FRIMAN M. FUJII S. HAPPINESS AND SATISFACTION WITH WORK COMMUTE (2013) | 2176 | 2327 |
| DE VOS J. SCHWANEN T. VAN ACKER V. WITLOX F. TRAVEL AND SUBJECTIVE WELL-BEING: A FOCUS ON FINDINGS METHODS AND FUTURE RESEARCH NEEDS (2013) | 2137 | 2312 |
| ETTEMA D. GÄRLING T. ERIKSSON L. FRIMAN M. OLSSON L.E. FUJII S. SATISFACTION WITH TRAVEL AND SUBJECTIVE WELL-BEING: DEVELOPMENT AND TEST OF A MEASU… | 2074 | 2194 |
| ST-LOUIS E. MANAUGH K. VAN LIEROP D. EL-GENEIDY A. THE HAPPY COMMUTER: A COMPARISON OF COMMUTER SATISFACTION ACROSS MODES (2014) | 2068 | 2229 |
| DE VOS J. MOKHTARIAN P.L. SCHWANEN T. VAN ACKER V. WITLOX F. TRAVEL MODE CHOICE AND TRAVEL SATISFACTION: BRIDGING THE GAP BETWEEN DECISION UTILITY … | 1794 | 2086 |
| ETTEMA D. GÄRLING T. OLSSON L.E. FRIMAN M. OUT-OF-HOME ACTIVITIES DAILY TRAVEL AND SUBJECTIVE WELL-BEING (2010) | 1772 | 1863 |
| YE R. TITHERIDGE H. SATISFACTION WITH THE COMMUTE: THE ROLE OF TRAVEL MODE CHOICE BUILT ENVIRONMENT AND ATTITUDES (2017) | 1604 | 1804 |
| MORRIS E.A. GUERRA E. MOOD AND MODE: DOES HOW WE TRAVEL AFFECT HOW WE FEEL? (2015) | 1412 | 1489 |
| FRIMAN M. FUJII S. ETTEMA D. GÄRLING T. OLSSON L.E. PSYCHOMETRIC ANALYSIS OF THE SATISFACTION WITH TRAVEL SCALE (2013) | 1410 | 1521 |
| ETTEMA D. FRIMAN M. GÄRLING T. OLSSON L.E. FUJII S. HOW IN-VEHICLE ACTIVITIES AFFECT WORK COMMUTERS’ SATISFACTION WITH PUBLIC TRANSPORT (2012) | 1046 | 1097 |
| Knowledge Base 7: KB 7: Wold cities networks (n = 623, density =5.5) | ||
| SASSEN S. (1991) | 965 | 1033 |
| FRIEDMANN J. THE WORLD CITY HYPOTHESIS (1986) | 797 | 803 |
| CASTELLS M. (1996) | 728 | 749 |
| TAYLOR P.J. SPECIFICATION OF THE WORLD CITY NETWORK (2001) | 453 | 453 |
| SASSEN S. (2001) | 450 | 465 |
| ALDERSON A.S. BECKFIELD J. POWER AND POSITION IN THE WORLD CITY SYSTEM (2004) | 429 | 429 |
| TAYLOR P.J. DERUDDER B. (2016) | 410 | 413 |
| ROBINSON J. GLOBAL AND WORLD CITIES: A VIEW FROM OFF THE MAP (2002) | 388 | 388 |
| BOURDIEU P. (1984) | 361 | 375 |
| BASSENS D. VAN MEETEREN M. WORLD CITIES UNDER CONDITIONS OF FINANCIALIZED GLOBALIZATION: TOWARDS AN AUGMENTED WORLD CITY HYPOTHESIS (2015) | 353 | 364 |
In a co-cittion network, the strength of the relationship between a reference pair \(m\) and \(n\) (\(s_{m,n}^{coc}\)) is expressed by the number of publications \(C\) which are jointly citing reference \(m\) and \(n\).
\[s_{m,n}^{coc} = \sum_i c_{i,m} c_{i,n}\]
The intuition here is that references which are frequently cited together are likely to share commonalities in theory, topic, methodology, or context. It can be interpreted as a measure of similarity as evaluated by other researchers that decide to jointly cite both references. Because the publication process is time-consuming, co-citation is a backward-looking measure, which is appropriate to map the relationship between core literature of a field.
This is arguably the more interesting part. Here, we identify the
literature’s current knowledge frontier by carrying out a bibliographic
coupling analysis of the publications in our corpus. This measure uses
bibliographical information of publications to establish a similarity
relationship between them. Again, method details to be found in the tab
Technical description. As you will see, we identify the
main research area, but also a set of adjacent research areas with some
theoretical/methodological/application overlap.
To identify communities in the field’s knowledge frontier (labeled research areas) we again use the Lovain Algorithm (Blondel et al., 2008). We identify the following communities = research areas.
| label | AU | PY | TI | dgr_int | TC | TC_year |
|---|---|---|---|---|---|---|
| Research Area 1: RA 1: Physical activities, health (n = 1023, density =0.15) | ||||||
| RA 1: Physical activities, health | DING D;LAWSON KD;KOLBE… | 2016 | THE ECONOMIC BURDEN OF PHYSICAL INACTIVITY: A GLOBAL ANALYSIS OF MAJOR NON-COMMUNICABLE DISEASES | 1.92 | 930 | 155.00 |
| RA 1: Physical activities, health | GUTHOLD R;STEVENS GA;R… | 2020 | GLOBAL TRENDS IN INSUFFICIENT PHYSICAL ACTIVITY AMONG ADOLESCENTS: A POOLED ANALYSIS OF 298 POPULATION-BASED SURVEYS WITH … | 1.60 | 722 | 361.00 |
| RA 1: Physical activities, health | LAIRD Y;FAWKNER S;KELL… | 2016 | THE ROLE OF SOCIAL SUPPORT ON PHYSICAL ACTIVITY BEHAVIOUR IN ADOLESCENT GIRLS: A SYSTEMATIC REVIEW AND META-ANALYSIS | 6.04 | 101 | 16.83 |
| RA 1: Physical activities, health | CHOI J;LEE M;LEE J-K;K… | 2017 | CORRELATES ASSOCIATED WITH PARTICIPATION IN PHYSICAL ACTIVITY AMONG ADULTS: A SYSTEMATIC REVIEW OF REVIEWS AND UPDATE | 4.71 | 128 | 25.60 |
| RA 1: Physical activities, health | GILES-CORTI B;VERNEZ-M… | 2016 | CITY PLANNING AND POPULATION HEALTH: A GLOBAL CHALLENGE | 0.91 | 516 | 86.00 |
| RA 1: Physical activities, health | TWOHIG-BENNETT C;JONES A | 2018 | THE HEALTH BENEFITS OF THE GREAT OUTDOORS: A SYSTEMATIC REVIEW AND META-ANALYSIS OF GREENSPACE EXPOSURE AND HEALTH OUTCOMES | 1.00 | 469 | 117.25 |
| RA 1: Physical activities, health | SALLIS JF;CERIN E;CONW… | 2016 | PHYSICAL ACTIVITY IN RELATION TO URBAN ENVIRONMENTS IN 14 CITIES WORLDWIDE: A CROSS-SECTIONAL STUDY | 0.75 | 599 | 99.83 |
| RA 1: Physical activities, health | CARLIN A;PERCHOUX C;PU… | 2017 | A LIFE COURSE EXAMINATION OF THE PHYSICAL ENVIRONMENTAL DETERMINANTS OF PHYSICAL ACTIVITY BEHAVIOUR: A “DETERMINANTS OF DI… | 7.21 | 60 | 12.00 |
| RA 1: Physical activities, health | LU C;STOLK RP;SAUER PJ… | 2017 | FACTORS OF PHYSICAL ACTIVITY AMONG CHINESE CHILDREN AND ADOLESCENTS: A SYSTEMATIC REVIEW | 6.06 | 71 | 14.20 |
| RA 1: Physical activities, health | CORDER K;SHARP SJ;ATKI… | 2016 | AGE-RELATED PATTERNS OF VIGOROUS-INTENSITY PHYSICAL ACTIVITY IN YOUTH: THE INTERNATIONAL CHILDREN’S ACCELEROMETRY DATABASE | 6.20 | 65 | 10.83 |
| Research Area 2: RA 2: Migration, economic growth (n = 883, density =0.17) | ||||||
| RA 2: Migration, economic growth | ACEMOGLU D;RESTREPO P | 2018 | THE RACE BETWEEN MAN AND MACHINE: IMPLICATIONS OF TECHNOLOGY FOR GROWTH, FACTOR SHARES, AND EMPLOYMENT | 3.68 | 313 | 78.25 |
| RA 2: Migration, economic growth | BHATTACHARYA M;AWAWORY… | 2017 | THE DYNAMIC IMPACT OF RENEWABLE ENERGY AND INSTITUTIONS ON ECONOMIC OUTPUT AND CO2 EMISSIONS ACROSS REGIONS | 1.82 | 272 | 54.40 |
| RA 2: Migration, economic growth | TEIXEIRA AAC;QUEIRÓS ASS | 2016 | ECONOMIC GROWTH, HUMAN CAPITAL AND STRUCTURAL CHANGE: A DYNAMIC PANEL DATA ANALYSIS | 3.00 | 160 | 26.67 |
| RA 2: Migration, economic growth | JONES CI | 2016 | THE FACTS OF ECONOMIC GROWTH | 4.56 | 100 | 16.67 |
| RA 2: Migration, economic growth | DIEBOLT C;HIPPE R | 2019 | THE LONG-RUN IMPACT OF HUMAN CAPITAL ON INNOVATION AND ECONOMIC DEVELOPMENT IN THE REGIONS OF EUROPE | 6.00 | 67 | 22.33 |
| RA 2: Migration, economic growth | BEINE M;BERTOLI S;FERN… | 2016 | A PRACTITIONERS’ GUIDE TO GRAVITY MODELS OF INTERNATIONAL MIGRATION | 2.83 | 135 | 22.50 |
| RA 2: Migration, economic growth | DIAMOND R | 2016 | THE DETERMINANTS AND WELFARE IMPLICATIONS OF US WORKERS’ DIVERGING LOCATION CHOICES BY SKILL: 1980-2000 | 1.64 | 231 | 38.50 |
| RA 2: Migration, economic growth | BEAUDRY P;GREEN DA;SAN… | 2016 | THE GREAT REVERSAL IN THE DEMAND FOR SKILL AND COGNITIVE TASKS | 2.90 | 118 | 19.67 |
| RA 2: Migration, economic growth | BOVE V;ELIA L | 2017 | MIGRATION, DIVERSITY, AND ECONOMIC GROWTH | 3.53 | 93 | 18.60 |
| RA 2: Migration, economic growth | BERG A;OSTRY JD;TSANGA… | 2018 | REDISTRIBUTION, INEQUALITY, AND GROWTH: NEW EVIDENCE | 4.24 | 73 | 18.25 |
| Research Area 3: RA 3: Travel behaviour, built environment (n = 829, density =0.4) | ||||||
| RA 3: Travel behaviour, built environment | DING C;WANG D;LIU C;ZH… | 2017 | EXPLORING THE INFLUENCE OF BUILT ENVIRONMENT ON TRAVEL MODE CHOICE CONSIDERING THE MEDIATING EFFECTS OF CAR OWNERSHIP AND … | 9.12 | 169 | 33.80 |
| RA 3: Travel behaviour, built environment | YE R;TITHERIDGE H | 2017 | SATISFACTION WITH THE COMMUTE: THE ROLE OF TRAVEL MODE CHOICE, BUILT ENVIRONMENT AND ATTITUDES | 9.51 | 162 | 32.40 |
| RA 3: Travel behaviour, built environment | ETTEMA D;NIEUWENHUIS R | 2017 | RESIDENTIAL SELF-SELECTION AND TRAVEL BEHAVIOUR: WHAT ARE THE EFFECTS OF ATTITUDES, REASONS FOR LOCATION CHOICE AND THE BU… | 13.91 | 76 | 15.20 |
| RA 3: Travel behaviour, built environment | MOURA F;CAMBRA P;GONÇA… | 2017 | MEASURING WALKABILITY FOR DISTINCT PEDESTRIAN GROUPS WITH A PARTICIPATORY ASSESSMENT METHOD: A CASE STUDY IN LISBON | 6.29 | 153 | 30.60 |
| RA 3: Travel behaviour, built environment | SUN B;ERMAGUN A;DAN B | 2017 | BUILT ENVIRONMENTAL IMPACTS ON COMMUTING MODE CHOICE AND DISTANCE: EVIDENCE FROM SHANGHAI | 6.89 | 122 | 24.40 |
| RA 3: Travel behaviour, built environment | EWING R;HAJRASOULIHA A… | 2016 | STREETSCAPE FEATURES RELATED TO PEDESTRIAN ACTIVITY | 8.30 | 101 | 16.83 |
| RA 3: Travel behaviour, built environment | CAO X;YANG W | 2017 | EXAMINING THE EFFECTS OF THE BUILT ENVIRONMENT AND RESIDENTIAL SELF-SELECTION ON COMMUTING TRIPS AND THE RELATED CO2 EMISS… | 11.20 | 72 | 14.40 |
| RA 3: Travel behaviour, built environment | SMITH M;HOSKING J;WOOD… | 2017 | SYSTEMATIC LITERATURE REVIEW OF BUILT ENVIRONMENT EFFECTS ON PHYSICAL ACTIVITY AND ACTIVE TRANSPORT - AN UPDATE AND NEW FI… | 2.49 | 283 | 56.60 |
| RA 3: Travel behaviour, built environment | DING C;WANG Y;TANG T;M… | 2018 | JOINT ANALYSIS OF THE SPATIAL IMPACTS OF BUILT ENVIRONMENT ON CAR OWNERSHIP AND TRAVEL MODE CHOICE | 9.99 | 60 | 15.00 |
| RA 3: Travel behaviour, built environment | LIN T;WANG D;GUAN X | 2017 | THE BUILT ENVIRONMENT, TRAVEL ATTITUDE, AND TRAVEL BEHAVIOR: RESIDENTIAL SELF-SELECTION OR RESIDENTIAL DETERMINATION? | 8.54 | 70 | 14.00 |
| Research Area 4: RA 4: Land use simulation modelling (n = 564, density =0.22) | ||||||
| RA 4: Land use simulation modelling | LIU X;LIANG X;LI X;XU … | 2017 | A FUTURE LAND USE SIMULATION MODEL (FLUS) FOR SIMULATING MULTIPLE LAND USE SCENARIOS BY COUPLING HUMAN AND NATURAL EFFECTS | 3.15 | 483 | 96.60 |
| RA 4: Land use simulation modelling | MUSTAFA A;HEPPENSTALL … | 2018 | MODELLING BUILT-UP EXPANSION AND DENSIFICATION WITH MULTINOMIAL LOGISTIC REGRESSION, CELLULAR AUTOMATA AND GENETIC ALGORITHM | 4.45 | 87 | 21.75 |
| RA 4: Land use simulation modelling | LIANG X;LIU X;LI X;CHE… | 2018 | DELINEATING MULTI-SCENARIO URBAN GROWTH BOUNDARIES WITH A CA-BASED FLUS MODEL AND MORPHOLOGICAL METHOD | 2.57 | 149 | 37.25 |
| RA 4: Land use simulation modelling | MISHRA VN;RAI PK | 2016 | A REMOTE SENSING AIDED MULTI-LAYER PERCEPTRON-MARKOV CHAIN ANALYSIS FOR LAND USE AND LAND COVER CHANGE PREDICTION IN PATNA… | 3.38 | 109 | 18.17 |
| RA 4: Land use simulation modelling | LIAO J;TANG L;SHAO G;S… | 2016 | INCORPORATION OF EXTENDED NEIGHBORHOOD MECHANISMS AND ITS IMPACT ON URBAN LAND-USE CELLULAR AUTOMATA SIMULATIONS | 5.09 | 72 | 12.00 |
| RA 4: Land use simulation modelling | SHAFIZADEH-MOGHADAM H;… | 2017 | COUPLING MACHINE LEARNING, TREE-BASED AND STATISTICAL MODELS WITH CELLULAR AUTOMATA TO SIMULATE URBAN GROWTH | 4.78 | 70 | 14.00 |
| RA 4: Land use simulation modelling | ABURAS MM;HO YM;RAMLI … | 2016 | THE SIMULATION AND PREDICTION OF SPATIO-TEMPORAL URBAN GROWTH TRENDS USING CELLULAR AUTOMATA MODELS: A REVIEW | 2.39 | 134 | 22.33 |
| RA 4: Land use simulation modelling | GHOSH P;MUKHOPADHYAY A… | 2017 | APPLICATION OF CELLULAR AUTOMATA AND MARKOV-CHAIN MODEL IN GEOSPATIAL ENVIRONMENTAL MODELING- A REVIEW | 3.39 | 89 | 17.80 |
| RA 4: Land use simulation modelling | VAN VLIET J;BREGT AK;B… | 2016 | A REVIEW OF CURRENT CALIBRATION AND VALIDATION PRACTICES IN LAND-CHANGE MODELING | 2.47 | 118 | 19.67 |
| RA 4: Land use simulation modelling | SHAFIZADEH-MOGHADAM H;… | 2017 | SENSITIVITY ANALYSIS AND ACCURACY ASSESSMENT OF THE LAND TRANSFORMATION MODEL USING CELLULAR AUTOMATA | 6.87 | 41 | 8.20 |
| Research Area 5: RA 5: Financial geography (n = 510, density =0.17) | ||||||
| RA 5: Financial geography | AALBERS MB | 2017 | THE VARIEGATED FINANCIALIZATION OF HOUSING | 3.28 | 147 | 29.40 |
| RA 5: Financial geography | FERNANDEZ R;AALBERS MB | 2016 | FINANCIALIZATION AND HOUSING: BETWEEN GLOBALIZATION AND VARIETIES OF CAPITALISM | 1.67 | 191 | 31.83 |
| RA 5: Financial geography | DERUDDER B;TAYLOR PJ | 2018 | CENTRAL FLOW THEORY: COMPARATIVE CONNECTIVITIES IN THE WORLD-CITY NETWORK | 3.77 | 68 | 17.00 |
| RA 5: Financial geography | FIELDS D | 2017 | UNWILLING SUBJECTS OF FINANCIALIZATION | 2.37 | 91 | 18.20 |
| RA 5: Financial geography | FIELDS D | 2017 | URBAN STRUGGLES WITH FINANCIALIZATION | 3.25 | 48 | 9.60 |
| RA 5: Financial geography | GABOR D;BROOKS S | 2017 | THE DIGITAL REVOLUTION IN FINANCIAL INCLUSION: INTERNATIONAL DEVELOPMENT IN THE FINTECH ERA | 0.78 | 191 | 38.20 |
| RA 5: Financial geography | PAN F;BI W;LENZER J;ZH… | 2017 | MAPPING URBAN NETWORKS THROUGH INTER-FIRM SERVICE RELATIONSHIPS: THE CASE OF CHINA | 2.51 | 54 | 10.80 |
| RA 5: Financial geography | DERUDDER B;TAYLOR P | 2016 | CHANGE IN THE WORLD CITY NETWORK, 2000–2012 | 2.97 | 45 | 7.50 |
| RA 5: Financial geography | FINE B;SAAD-FILHO A | 2017 | THIRTEEN THINGS YOU NEED TO KNOW ABOUT NEOLIBERALISM | 1.17 | 111 | 22.20 |
| RA 5: Financial geography | SIGLER TJ;MARTINUS K | 2017 | EXTENDING BEYOND ‘WORLD CITIES’ IN WORLD CITY NETWORK (WCN) RESEARCH: URBAN POSITIONALITY AND ECONOMIC LINKAGES THROUGH TH… | 2.45 | 52 | 10.40 |
| Research Area 6: RA 6: Cross-border integration (n = 445, density =0.12) | ||||||
| RA 6: Cross-border integration | FRIEDMAN S | 2016 | HABITUS CLIVÉ AND THE EMOTIONAL IMPRINT OF SOCIAL MOBILITY | 0.82 | 142 | 23.67 |
| RA 6: Cross-border integration | MEIJERS MJ | 2017 | CONTAGIOUS EUROSCEPTICISM: THE IMPACT OF EUROSCEPTIC SUPPORT ON MAINSTREAM PARTY POSITIONS ON EUROPEAN INTEGRATION | 0.79 | 94 | 18.80 |
| RA 6: Cross-border integration | DECOTEAU CL | 2016 | THE REFLEXIVE HABITUS: CRITICAL REALIST AND BOURDIEUSIAN SOCIAL ACTION | 1.07 | 58 | 9.67 |
| RA 6: Cross-border integration | MUDDE C | 2016 | ON EXTREMISM AND DEMOCRACY IN EUROPE | 0.76 | 81 | 13.50 |
| RA 6: Cross-border integration | DECOVILLE A;DURAND F | 2019 | EXPLORING CROSS-BORDER INTEGRATION IN EUROPE: HOW DO POPULATIONS CROSS BORDERS AND PERCEIVE THEIR NEIGHBOURS? | 2.00 | 23 | 7.67 |
| RA 6: Cross-border integration | CASTELLÓ E;MIHELJ S | 2018 | SELLING AND CONSUMING THE NATION: UNDERSTANDING CONSUMER NATIONALISM | 1.02 | 45 | 11.25 |
| RA 6: Cross-border integration | RAUCHFLEISCH A | 2017 | THE PUBLIC SPHERE AS AN ESSENTIALLY CONTESTED CONCEPT: A CO-CITATION ANALYSIS OF THE LAST 20 YEARS OF PUBLIC SPHERE RESEARCH | 2.27 | 18 | 3.60 |
| RA 6: Cross-border integration | SOHN C | 2016 | NAVIGATING BORDERS’ MULTIPLICITY: THE CRITICAL POTENTIAL OF ASSEMBLAGE | 1.01 | 38 | 6.33 |
| RA 6: Cross-border integration | PIRRO ALP;TAGGART P | 2018 | THE POPULIST POLITICS OF EUROSCEPTICISM IN TIMES OF CRISIS: A FRAMEWORK FOR ANALYSIS | 0.84 | 43 | 10.75 |
| RA 6: Cross-border integration | LAINE JP | 2016 | THE MULTISCALAR PRODUCTION OF BORDERS | 0.48 | 73 | 12.17 |
| Research Area 7: RA 7: Travel behaviour, well-being (n = 361, density =0.74) | ||||||
| RA 7: Travel behaviour, well-being | DE VOS J;MOKHTARIAN PL… | 2016 | TRAVEL MODE CHOICE AND TRAVEL SATISFACTION: BRIDGING THE GAP BETWEEN DECISION UTILITY AND EXPERIENCED UTILITY | 6.74 | 193 | 32.17 |
| RA 7: Travel behaviour, well-being | DE VOS J | 2020 | THE EFFECT OF COVID-19 AND SUBSEQUENT SOCIAL DISTANCING ON TRAVEL BEHAVIOR | 3.10 | 367 | 183.50 |
| RA 7: Travel behaviour, well-being | DE VOS J;WITLOX F | 2017 | TRAVEL SATISFACTION REVISITED. ON THE PIVOTAL ROLE OF TRAVEL SATISFACTION IN CONCEPTUALISING A TRAVEL BEHAVIOUR PROCESS | 11.94 | 78 | 15.60 |
| RA 7: Travel behaviour, well-being | CHATTERJEE K;CHNG S;CL… | 2020 | COMMUTING AND WELLBEING: A CRITICAL OVERVIEW OF THE LITERATURE WITH IMPLICATIONS FOR POLICY AND FUTURE RESEARCH | 9.47 | 87 | 43.50 |
| RA 7: Travel behaviour, well-being | SINGLETON PA | 2019 | WALKING (AND CYCLING) TO WELL-BEING: MODAL AND OTHER DETERMINANTS OF SUBJECTIVE WELL-BEING DURING THE COMMUTE | 9.65 | 82 | 27.33 |
| RA 7: Travel behaviour, well-being | FRIMAN M;GÄRLING T;ETT… | 2017 | HOW DOES TRAVEL AFFECT EMOTIONAL WELL-BEING AND LIFE SATISFACTION? | 8.46 | 84 | 16.80 |
| RA 7: Travel behaviour, well-being | DE VOS J | 2019 | ANALYSING THE EFFECT OF TRIP SATISFACTION ON SATISFACTION WITH THE LEISURE ACTIVITY AT THE DESTINATION OF THE TRIP, IN REL… | 9.71 | 66 | 22.00 |
| RA 7: Travel behaviour, well-being | DE VOS J | 2018 | DO PEOPLE TRAVEL WITH THEIR PREFERRED TRAVEL MODE? ANALYSING THE EXTENT OF TRAVEL MODE DISSONANCE AND ITS EFFECT ON TRAVEL… | 9.70 | 64 | 16.00 |
| RA 7: Travel behaviour, well-being | ZHU J;FAN Y | 2018 | COMMUTE HAPPINESS IN XI’AN, CHINA: EFFECTS OF COMMUTE MODE, DURATION, AND FREQUENCY | 11.50 | 53 | 13.25 |
| RA 7: Travel behaviour, well-being | ZHU J;FAN Y | 2018 | DAILY TRAVEL BEHAVIOR AND EMOTIONAL WELL-BEING: EFFECTS OF TRIP MODE, DURATION, PURPOSE, AND COMPANIONSHIP | 8.79 | 65 | 16.25 |
| Research Area 8: RA 8: Transport mode choices (n = 312, density =0.36) | ||||||
| RA 8: Transport mode choices | DE HAAS M;FABER R;HAME… | 2020 | HOW COVID-19 AND THE DUTCH ‘INTELLIGENT LOCKDOWN’ CHANGE ACTIVITIES, WORK AND TRAVEL BEHAVIOUR: EVIDENCE FROM LONGITUDINAL… | 1.71 | 225 | 112.50 |
| RA 8: Transport mode choices | LANZINI P;KHAN SA | 2017 | SHEDDING LIGHT ON THE PSYCHOLOGICAL AND BEHAVIORAL DETERMINANTS OF TRAVEL MODE CHOICE: A META-ANALYSIS | 3.11 | 102 | 20.40 |
| RA 8: Transport mode choices | ZHAO P;LI S | 2017 | BICYCLE-METRO INTEGRATION IN A GROWING CITY: THE DETERMINANTS OF CYCLING AS A TRANSFER MODE IN METRO STATION AREAS IN BEIJING | 2.79 | 107 | 21.40 |
| RA 8: Transport mode choices | KROESEN M;HANDY S;CHOR… | 2017 | DO ATTITUDES CAUSE BEHAVIOR OR VICE VERSA? AN ALTERNATIVE CONCEPTUALIZATION OF THE ATTITUDE-BEHAVIOR RELATIONSHIP IN TRAVE… | 2.11 | 138 | 27.60 |
| RA 8: Transport mode choices | MUÑOZ B;MONZON A;LÓPEZ E | 2016 | TRANSITION TO A CYCLABLE CITY: LATENT VARIABLES AFFECTING BICYCLE COMMUTING | 3.95 | 66 | 11.00 |
| RA 8: Transport mode choices | FERNÁNDEZ-HEREDIA Á;JA… | 2016 | MODELLING BICYCLE USE INTENTION: THE ROLE OF PERCEPTIONS | 3.03 | 50 | 8.33 |
| RA 8: Transport mode choices | VIJ A;WALKER JL | 2016 | HOW, WHEN AND WHY INTEGRATED CHOICE AND LATENT VARIABLE MODELS ARE LATENTLY USEFUL | 1.02 | 140 | 23.33 |
| RA 8: Transport mode choices | ZAILANI S;IRANMANESH M… | 2016 | IS THE INTENTION TO USE PUBLIC TRANSPORT FOR DIFFERENT TRAVEL PURPOSES DETERMINED BY DIFFERENT FACTORS? | 2.41 | 57 | 9.50 |
| RA 8: Transport mode choices | HOFFMANN C;ABRAHAM C;W… | 2017 | WHAT COGNITIVE MECHANISMS PREDICT TRAVEL MODE CHOICE? A SYSTEMATIC REVIEW WITH META-ANALYSIS | 2.66 | 50 | 10.00 |
| RA 8: Transport mode choices | CASS N;FAULCONBRIDGE J | 2016 | COMMUTING PRACTICES: NEW INSIGHTS INTO MODAL SHIFT FROM THEORIES OF SOCIAL PRACTICE | 1.18 | 104 | 17.33 |
| Research Area 9: RA 9: Housing prices, property values (n = 289, density =0.28) | ||||||
| RA 9: Housing prices, property values | BELTRÁN A;MADDISON D;E… | 2018 | IS FLOOD RISK CAPITALISED INTO PROPERTY VALUES? | 2.48 | 52 | 13.00 |
| RA 9: Housing prices, property values | ZHANG L | 2016 | FLOOD HAZARDS IMPACT ON NEIGHBORHOOD HOUSE PRICES: A SPATIAL QUANTILE REGRESSION ANALYSIS | 2.24 | 57 | 9.50 |
| RA 9: Housing prices, property values | YEH I-C;HSU T-K | 2018 | BUILDING REAL ESTATE VALUATION MODELS WITH COMPARATIVE APPROACH THROUGH CASE-BASED REASONING | 2.19 | 46 | 11.50 |
| RA 9: Housing prices, property values | ABIDOYE RB;CHAN APC | 2018 | IMPROVING PROPERTY VALUATION ACCURACY: A COMPARISON OF HEDONIC PRICING MODEL AND ARTIFICIAL NEURAL NETWORK | 2.70 | 32 | 8.00 |
| RA 9: Housing prices, property values | KOUSKY C | 2018 | FINANCING FLOOD LOSSES: A DISCUSSION OF THE NATIONAL FLOOD INSURANCE PROGRAM | 1.34 | 44 | 11.00 |
| RA 9: Housing prices, property values | BELTRÁN A;MADDISON D;E… | 2019 | THE IMPACT OF FLOODING ON PROPERTY PRICES: A REPEAT-SALES APPROACH | 2.81 | 20 | 6.67 |
| RA 9: Housing prices, property values | ABIDOYE RB;CHAN APC | 2017 | ARTIFICIAL NEURAL NETWORK IN PROPERTY VALUATION: APPLICATION FRAMEWORK AND RESEARCH TREND | 2.11 | 26 | 5.20 |
| RA 9: Housing prices, property values | ABIDOYE RB;CHAN APC | 2017 | MODELLING PROPERTY VALUES IN NIGERIA USING ARTIFICIAL NEURAL NETWORK | 2.52 | 21 | 4.20 |
| RA 9: Housing prices, property values | HONG J;CHOI H;KIM W-S | 2020 | A HOUSE PRICE VALUATION BASED ON THE RANDOM FOREST APPROACH: THE MASS APPRAISAL OF RESIDENTIAL PROPERTY IN SOUTH KOREA | 2.07 | 22 | 11.00 |
| RA 9: Housing prices, property values | VOTSIS A;PERRELS A | 2016 | HOUSING PRICES AND THE PUBLIC DISCLOSURE OF FLOOD RISK: A DIFFERENCE-IN-DIFFERENCES ANALYSIS IN FINLAND | 1.66 | 27 | 4.50 |
In a bibliographic coupling network, the coupling-strength between publications is determined by the number of commonly cited references they share, assuming a common pool of references to indicate similarity in context, methods, or theory. Formally, the strength of the relationship between a publication pair \(i\) and \(j\) (\(s_{i,j}^{bib}\)) is expressed by the number of commonly cited references.
\[s_{i,j}^{bib} = \sum_m c_{i,m} c_{j,m}\]
Since our corpus contains publications which differ strongly in terms of the number of cited references, we normalize the coupling strength by the Jaccard similarity coefficient. Here, we weight the intercept of two publications’ bibliography (shared refeences) by their union (number of all references cited by either \(i\) or \(j\)). It is bounded between zero and one, where one indicates the two publications to have an identical bibliography, and zero that they do not share any cited reference. Thereby, we prevent publications from having high coupling strength due to a large bibliography (e.g., literature surveys).
\[S_{i,j}^{jac-bib} =\frac{C(i \cap j)}{C(i \cup j)} = \frac{s_{i,j}^{bib}}{c_i + c_j - s_{i,j}^{bib}}\]
More recent articles have a higher pool of possible references to co-cite to, hence they are more likely to be coupled. Consequently, bibliographic coupling represents a forward looking measure, and the method of choice to identify the current knowledge frontier at the point of analysis.
All results are preliminary so far…